Cloud networking company Cato Networks Ltd. today announced the launch of Cato Dynamic Prevention, an auto-adaptive threat prevention engine that allows enterprises to proactively block advanced threats using legitimate tools and targets.

The new offering continuously evaluates activity in full context and correlates signals from across Cato’s sensors over months of activity. Once malicious behavior is identified, Cato automatically adapts and enforces restrictions across related actions from threat actors, stopping threats early without adding operational overhead or requiring information technology or security operations center intervention.

Advanced attacks increasingly blend into normal enterprise activity by abusing legitimate tools and targets. Rather than triggering a single high-confidence alert, threat actors execute a series of low-signal actions over time, each appearing benign in isolation. That approach allows malicious behavior to evade traditional, point-in-time inspection and remain undetected during the early and most preventable stages of an attack.

Cato argues that existing security point solutions are typically not built to identify these patterns, as they operate in silos and lack the context needed to correlate activity across time, hosts and networks. Added to the mix is that even when threats are eventually detected, response is often manual and delayed, giving threat actors time to persist, move laterally and escalate impact.

Dynamic Prevention closes the gap by identifying and automatically stopping advanced threats that evade point-in-time inspection.

The new service is built into the Cato SASE Platform and continuously correlates months of security and networking activity in real time across the company’s full range of inline sensors to identify behavior-based threats that appear benign in isolation. Once identified, Cato dynamically applies adaptive rules, blocking high-risk activity in real time.

Using Dynamic Prevention, it says, enterprises gain reduced risk exposure, a strong security posture and greater IT and SOC efficiency.

“Threat actors abuse trusted tools and valid credentials, knowing most defenses still analyze isolated events and rely on humans to connect the dots for more complex attack chains,” said Lior Cohen, Cato’s vice president of product management, security and management. “Cato Dynamic Prevention changes the game by continuously understanding behavior in context, predicting the threat actor’s next move and enforcing protection automatically that would only impact true positive threats. As a result, this stops potential threats before a breach ever takes shape.”

Daniela Rosenstein, agentic AI and RPA lead at Cato Networks, and Taqi Jaffri, senior director of product management at UiPath Inc., spoke with theCUBE, SiliconANGLE Media’s livestreaming studio, in October, when they discussed how agentic AI delivers real return on investment with focused use cases.

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